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self hosted llm

Self-hosted LLM for controlled local execution

This page is for the self-hosted LLM buyer who wants local deployment and tighter operator control, not just a reworded 'offline AI' claim.

OpenJet gives teams a self-hosted LLM interface that runs near the hardware it serves. The model is local, the tool runtime is local, and the operator stays in control of state-changing actions.

Why local wins

  • Self-hosted by design. Run local GGUF and hardware-optimized backends on Jetson and Linux systems without routing prompts to a hosted API.
  • Operator remains in control. OpenJet is structured around approved execution, which is a better pattern for sensitive systems than letting an LLM act unchecked.
  • Best as a wrapper over trusted scripts. The strongest pattern is to use natural language to find the right evidence and run pre-verified procedures already staged on the device.

Common deployment paths

  • Deploy a self-hosted LLM on your own Jetson or Linux hardware instead of relying on a hosted API.
  • Give operators a local AI interface without allowing free-form code generation on critical systems.
  • Use natural language to surface and run trusted operational scripts under human approval.

FAQ

What makes OpenJet a self-hosted LLM solution?
OpenJet runs the model and the operating interface locally on your own hardware, rather than sending prompts and evidence to a managed API.
How is this different from a generic self-hosted chat UI?
OpenJet is aimed at operational workflows: local logs, local scripts, local approval, and local execution close to the system being managed.
Should OpenJet be used to let the model write new code on mission-critical hardware?
No. The better pattern is to let OpenJet help the human find the right script or procedure, then require approval before anything state-changing runs.

Read the docs or go back to the homepage.